Conduct seamless analysis across multiple brand datasets to power rich industry insights, without transferring data to each other or a third-party.
Enable media agencies and other partners to safely access insights from first-party data to enable data-driven planning, creative and buying decisions.
Connect publisher data to establish a unified audience that can be made available for brands to analyse, segment and target.
We don’t hold any data. We provide the identity infrastructure to power a decentralised ecosystem.
Federated technology keeps your data in its own unique Bunker, that only you can access.
You remain in control of who can analyse your data. This never grants access to the raw data.
First-party data sets are matched using existing identifiers, removing the need to share data.
A group of leading UK based publishers plan to establish a data alliance to provide a combined solution that will allow brands to activate against their unified audience to empower brands to reach more scale. There are a number of issues preventing this initiative from moving forward:
Each publisher uploads their customer data to their own isolated Bunker. The data goes through InfoSum’s AI-powered normalisation and mapping process.
An automated process matches identities using existing identifiers, removing the need for a universal ID. (Where a match can not be made, a third-party identity graph may be used to supplement a match, but doesn’t require data to be transferred to the identity graph owner.)
Each Bunker owner grants permission to a nominated user. This user is now able to conduct statistical analysis across the unified audience data.
This approach overcomes the commercial trust issues, as no individual in the unified audience is ever identified, and the decentralised nature of InfoSum’s platform means data is never shared.
It is now possible for the unified audience to be made available for brands to conduct analysis against, build segments, and conduct privacy-safe activation.
Aggregate level results and differential privacy features prevent any single individual being identified within a dataset.
Federated Architecture and Insights Engine overcomes trust barriers by removing the need to share and centralise data.
AI-powered normalisation and mapping removes the need for a complex and expensive ETL projects.
Each party retains complete control over their data through decentralisation and rich permission controls.